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  1. import stormpy
  2. import stormpy.core
  3. import stormpy.simulator
  4. import stormpy.examples
  5. import stormpy.examples.files
  6. import random
  7. """
  8. Simulator for nondeterministic models
  9. """
  10. def example_simulator_02():
  11. path = stormpy.examples.files.prism_mdp_maze
  12. prism_program = stormpy.parse_prism_program(path)
  13. model = stormpy.build_model(prism_program)
  14. simulator = stormpy.simulator.create_simulator(model, seed=42)
  15. # 5 paths of at most 20 steps.
  16. paths = []
  17. for m in range(5):
  18. path = []
  19. state, reward = simulator.restart()
  20. path = [f"{state}"]
  21. for n in range(20):
  22. actions = simulator.available_actions()
  23. select_action = random.randint(0,len(actions)-1)
  24. #print(f"Randomly select action nr: {select_action} from actions {actions}")
  25. path.append(f"--act={actions[select_action]}-->")
  26. state, reward = simulator.step(actions[select_action])
  27. #print(state)
  28. path.append(f"{state}")
  29. if simulator.is_done():
  30. #print("Trapped!")
  31. break
  32. paths.append(path)
  33. for path in paths:
  34. print(" ".join(path))
  35. options = stormpy.BuilderOptions()
  36. options.set_build_state_valuations()
  37. options.set_build_choice_labels(True)
  38. model = stormpy.build_sparse_model_with_options(prism_program, options)
  39. print(model)
  40. simulator = stormpy.simulator.create_simulator(model, seed=42)
  41. simulator.set_observation_mode(stormpy.simulator.SimulatorObservationMode.PROGRAM_LEVEL)
  42. simulator.set_action_mode(stormpy.simulator.SimulatorActionMode.GLOBAL_NAMES)
  43. # 5 paths of at most 20 steps.
  44. paths = []
  45. for m in range(5):
  46. path = []
  47. state, reward = simulator.restart()
  48. path = [f"{state}"]
  49. for n in range(20):
  50. actions = simulator.available_actions()
  51. select_action = random.randint(0,len(actions)-1)
  52. #print(f"Randomly select action nr: {select_action} from actions {actions}")
  53. path.append(f"--act={actions[select_action]}-->")
  54. state, reward = simulator.step(actions[select_action])
  55. #print(state)
  56. path.append(f"{state}")
  57. if simulator.is_done():
  58. #print("Trapped!")
  59. break
  60. paths.append(path)
  61. for path in paths:
  62. print(" ".join(path))
  63. if __name__ == '__main__':
  64. example_simulator_02()